Kinship, Intelligence, and Memory as Improvisation: Culture and Performance in New Orleans
Bibliographic record
Abstract
Pierre Hèbert Born in Montreal in 1944, Pierre Hébert taught himself as a teenager how to make films, strongly influenced by the work of Norman McLaren and Len Lye; as he says to Nicholas Loess in this volume, “I saw myself as an artist using film amongst a number of things.” In 1962 he began experimenting with engraving images directly onto processed 16mm or 35mm film. At the National Film Board of Canada from 1965 until 1999, in Population Explosion (1968) Hébert collaborated with Ornette Coleman, and, gradually in such films as Entre chiens et loup (1978) and Memories of War (1982), his work became more socially and politically involved. In 1983 he began collaborating in live performance with improvising musicians (Jean Derome, Robert M. Lepage, René Lussier, Fred Frith) and choreographers (Ginette Laurin, Rosalind Newman, Louise Bédard, and Jean-Marc Matos), finding that his own efforts to improvise within the film medium led to the development of other kinds of skills. He is currently using computers in the Living Cinema project with composer Bob Ostertag, and furthering his long-time interest in the relationships between animation and live action in his “Places and Monuments.” In 2006 a collection of Hébert’s writings on film were published as Corps, langage, technologie .
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.014 | 0.015 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".